/// @file
/// @author David Pilger <dpilger26@gmail.com>
/// [GitHub Repository](https://github.com/dpilger26/NumCpp)
/// @version 1.3
///
/// @section License
/// Copyright 2020 David Pilger
///
/// Permission is hereby granted, free of charge, to any person obtaining a copy of this
/// software and associated documentation files(the "Software"), to deal in the Software
/// without restriction, including without limitation the rights to use, copy, modify,
/// merge, publish, distribute, sublicense, and/or sell copies of the Software, and to
/// permit persons to whom the Software is furnished to do so, subject to the following
/// conditions :
///
/// The above copyright notice and this permission notice shall be included in all copies
/// or substantial portions of the Software.
///
/// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
/// INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
/// PURPOSE AND NONINFRINGEMENT.IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE
/// FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
/// OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
/// DEALINGS IN THE SOFTWARE.
///
/// @section Description
/// Calculates a multidimensional kernel convolution.
///
#pragma once

#include "NumCpp/Core/Error.hpp"
#include "NumCpp/Core/Shape.hpp"
#include "NumCpp/Core/Slice.hpp"
#include "NumCpp/Core/Types.hpp"
#include "NumCpp/Filter/Boundaries/Boundary.hpp"
#include "NumCpp/Filter/Boundaries/Boundaries2d/addBoundary2d.hpp"
#include "NumCpp/NdArray.hpp"
#include "NumCpp/Functions/dot.hpp"
#include "NumCpp/Functions/rot90.hpp"
#include "NumCpp/Utils/sqr.hpp"

#include <string>

namespace nc
{
    namespace filter
    {
        //============================================================================
        // Method Description:
        ///						Calculates a multidimensional kernel convolution.
        ///
        ///                     SciPy Reference: https://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.convolve.html#scipy.ndimage.convolve
        ///
        /// @param				inImageArray
        /// @param				inSize: square size of the kernel to apply
        /// @param              inWeights
        /// @param              inBoundaryType: boundary mode (default Reflect) options (reflect, constant, nearest, mirror, wrap)
        /// @param				inConstantValue: contant value if boundary = 'constant' (default 0)
        /// @return
        ///				NdArray
        ///
        template<typename dtype>
        NdArray<dtype> convolve(const NdArray<dtype>& inImageArray, uint32 inSize,
            const NdArray<dtype>& inWeights, Boundary inBoundaryType = Boundary::REFLECT, dtype inConstantValue = 0)
        {
            if (inWeights.size() != utils::sqr(inSize))
            {
                THROW_INVALID_ARGUMENT_ERROR("input weights do no match input kernal size.");
            }

            NdArray<dtype> arrayWithBoundary = boundary::addBoundary2d(inImageArray, inBoundaryType, inSize, inConstantValue);
            NdArray<dtype> output(inImageArray.shape());

            NdArray<dtype> weightsFlat = rot90(inWeights, 2).flatten();
            const Shape inShape = inImageArray.shape();
            const uint32 boundarySize = inSize / 2; // integer division
            const uint32 endPointRow = boundarySize + inShape.rows;
            const uint32 endPointCol = boundarySize + inShape.cols;

            for (uint32 row = boundarySize; row < endPointRow; ++row)
            {
                for (uint32 col = boundarySize; col < endPointCol; ++col)
                {
                    NdArray<dtype> window = arrayWithBoundary(Slice(row - boundarySize, row + boundarySize + 1),
                        Slice(col - boundarySize, col + boundarySize + 1)).flatten();

                    output(row - boundarySize, col - boundarySize) = dot(window, weightsFlat).item();
                }
            }

            return output;
        }
    }
}
